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EP-4735632-A1 - HIGH-ACCURACY QUANTIFICATION OF NUCLEIC ACIDS FROM PRE-DEFINED AMOUNTS OF CELLS USING PLATE-BASED DIGITIAL PCR

EP4735632A1EP 4735632 A1EP4735632 A1EP 4735632A1EP-4735632-A1

Abstract

The present invention relates to a method of quantifying the amount of at least one nucleic acid target, the method comprising: a) Providing a defined number of cells, wherein the defined number of cells is at least one cell; and b) Lysing the at least one cell, thereby releasing RNA and DNA; and c) Performing a reverse transcription reaction on the released RNA, thereby generating complementary DNA (cDNA), and further performing a digital polymerase chain reaction (dPCR) on at least one reverse transcribed RNA target within the cDNA; and/or performing a digital polymerase chain reaction (dPCR) on at least one DNA target within the released DNA, wherein the dPCR is performed in a plate; and d) Quantifying the amount of the at least one nucleic acid target.

Inventors

  • KARALAY-KARABIBER, Özlem
  • ALBERS, Julius
  • MARTORANA, Domenica
  • THORN, JONATHAN

Assignees

  • QIAGEN GmbH

Dates

Publication Date
20260506
Application Date
20240626

Claims (15)

  1. 1. A method of quantifying the amount of at least one nucleic acid target, the method comprising: e) Providing a defined number of cells, wherein the defined number of cells is at least one cell; and f) Lysing the at least one cell, thereby releasing RNA and DNA; and g) Performing a reverse transcription reaction on the released RNA, thereby generating complementary DNA (cDNA), and further performing a digital polymerase chain reaction (dPCR) on at least one reverse transcribed RNA target within the cDNA; and/or performing a digital polymerase chain reaction (dPCR) on at least one DNA target within the released DNA, wherein the dPCR is performed in a plate; and h) Quantifying the amount of the at least one nucleic acid target.
  2. 2. The method according to claim 1, wherein the provided at least one cell is directly isolated into lysis buffer.
  3. 3. The method according to any of the preceding claims, wherein each of the at least one nucleic acid targets is independently selected from a coding RNA target; a non-coding RNA target; a genomic DNA target; and a mitochondrial DNA target.
  4. 4. The method according to claim 3, wherein the coding RNA target is an mRNA; the non-coding RNA target is a miRNA; the genomic DNA target is a region on genomic DNA, that harbors or is suspected to harbor a copy number variation (CNV); and the mitochondrial DNA target is a region on mitochondrial DNA, that harbors or is suspected to harbor a CNV.
  5. 5. The method according to any of the preceding claims, wherein the at least one cell is provided by a method selected from the group consisting of fluorescence-activated cell sorting, micromanipulation, microfluidics, immunopanning, magnet-activated cell sorting, and laser microdissectioning.
  6. 6. The method according to any of the preceding claims, wherein the dPCR is performed in a Nanoplate.
  7. 7. The method according to any of the preceding claims, wherein the dPCR is performed simultaneously on one target, or on two targets, or on three targets, or on four targets, or on five targets within the cDNA and/or the released DNA.
  8. 8. The method according to any of the preceding claims, wherein each of the at least one nucleic acid targets is independently selected from the group consisting of a low-copy target, a medium-copy target, and a high-copy target.
  9. 9. The method according to any of the preceding claims, wherein quantification is based on the detection of the amplified at least one nucleic acid target by using at least one probe per analyzed target, wherein the at least one probe specifically binds to each of the amplification products per nucleic acid target.
  10. 10. The method according to claim 9, wherein the at least one probe is fluorescently labelled.
  11. 11. The method according to claim 10, wherein the at least one probe is at least one TaqMan probe.
  12. 12. The method according to any of the preceding claims, wherein the quantification result of the at least one target is compared with the quantification result of said at least one target within the cDNA and/or the released DNA of at least one further cell.
  13. 13. The method according to any of the preceding claims, wherein the at least one cell originates from a eukaryotic sample, preferably a human sample.
  14. 14. The method according to claim 13, wherein the human sample originates from a subject having cancer or being suspected of having cancer.
  15. 15. The method according to claim 13, wherein the human sample originates from a subject having or suspected of having a disease.

Description

HIGH-ACCURACY QUANTIFICATION OF NUCLEIC ACIDS FROM PRE-DEFINED AMOUNTS OF CELLS USING PLATE-BASED DIGITIAL PCR FIELD OF INVENTION The present invention is in the field of molecular biology, in particular in the field of targeted nucleic acid analysis. More specifically, the invention is in the field of mRNA and miRNA expression analysis as well as targeted genomic and mitochondrial copy number variation analysis, wherein a specific amount of cells is isolated and nucleic acids are quantified using plate-based digital PCR. BACKGROUND Single cell analyses allow researchers to uncover new information and gain novel insights into biological processes of an individual cell in comparison to traditional methods analyzing cell populations in bulk. Thus, individual cell heterogeneity can be analyzed rather than the average output of the cell population. Drastic cell to cell variation can be observed especially at the level of transcriptome even though cells are identical on a genetic and morphological level. Capturing this transcriptomic heterogeneity is particularly important for disease and drug development studies where the differences in biological response to drugs from individual cells versus from tissues might provide additional insights into the disease progression or prevention. Intricate transcriptional networks can be outlined to generate improved drug response models. In addition to disease and drug screening therapies, single cell transcript analyses can be applied to e.g. aging, stem cell, gene and cell therapies, prenatal screening, organoid studies, as well as infectious disease studies among others. Capturing cell heterogeneity is also important for detection of naturally occurring mutations, chromosomal rearrangements or copy number variation (CNV; or copy number alterations (CNA)) events within cells. CNVs are structural changes in genome (such as deletions, insertions, duplications, translocations, and inversions) that lead to gain or loss of copy numbers of a region, ranging from a few base pairs to a few hundred base pairs up to whole chromosomes. CNVs are either inherited or the results of de novo somatic changes. Responsible for up to 10-20% variation in the genome, CNVs are a source of natural genetic diversity as well as biological dysfunction in humans. CNVs often result in disruption of gene function, dosage imbalances, shortening of chromosomal ends and positional effects, which are associated with complex diseases and traits such as cancer, obesity, aging and neurodegenerative and autoimmune diseases. The quantitative analyses of CNVs at disease-associated loci, therefore, provide insights into molecular mechanisms of diseases and offer potential for the discovery of novel biomarkers. Similar to genomic DNA copy number (gDNA CN) alterations, changes in mitochondrial DNA copy number (mtDNA CN) in blood or tissue have been linked to diseases, not surprisingly given the important role mitochondria play in cellular homeostasis. In contrast to fixed copy number of genomic DNA (healthy diploid state), drastic cell to cell variation can be observed at the level of mitochondrial DNA (mtDNA), even though cells are identical in genetic identity and morphology. mtDNA copy numbers fluctuate and vary between individuals, as well as between different tissues, cells and even among mitochondria within the same cell. Individual cells can carry hundreds to hundred thousand copies of mtDNA. However, the drastic changes in copy number of mtDNA can lead to mitochondrial dysfunction and disease formation. Therefore, similar to genomic CNVs, capturing the copy number heterogeneity in mtDNA is important for disease and drug development studies and can be used as a proxy for screening metabolic diseases, cancer, prenatal testing, neurodegeneration, and aging-related diseases. Moreover, single cell CNV analyses can be applied to gene and cell therapies, CAR-T therapies, intentional or unintentional (off-target effects during gene editing) gene alterations induced by viral vectors or CRISPR modifications, organoid studies, quantification of organelles as well as infectious disease studies. Additionally, non-coding RNAs are actively involved in cell function and specialization. miRNAs, for example, are important non-coding, well conserved, post-transcriptional regulators with a great potential as diagnostic or prognostic biomarkers. The most recent miRbase release lists 2654 annotated human miRNAs. Drastic cell to cell variation can be observed not only on mRNA transcript level, but also on (small) non-coding RNA (such as miRNAs) transcript level, even if cells are identical on a genetic and morphological level. Furthermore, each individual cell provides a unique microenvironment. miRNA expression profiles give insights on cellular states (e.g., human cancers) and cellular mechanisms. miRNAs are known to regulate the expression of up to 1/3 of the encoded human genes and with that to influence a wide range of